Part 2: Application of Kanaya–Okayama heat source in modelling micro electron beam welding
Bibliographic record
Abstract
A three-dimensional finite element model of micro electron beam welding is developed where the Kanaya–Okayama heat source formulated in Part I of this work is used to represent the electron beam. The large number of process variables is grouped into two non-dimensional parameters, namely, Peclet number and relative beam penetration, and their effect is analysed numerically to arrive at the optimum conditions of microwelding. Based on the minimum heat input of the process, the optimum Peclet number is found to be 100, and the beam penetration is twice that of the weld depth. The optimum parameters obtained using the Kanaya–Okayama heat source model are similar to the previous findings using the exponential decay heat source model; however, the predictions of the temperature field in the solid as a result of microwelding are relatively lower in case of the Kanaya–Okayama heat source model because of the differences in distribution of heat into the condensed matter. The lower weld surface temperatures in microwelding using the electron beam suggest significantly less ablation than in laser beams.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".